where \(\mathcal {L}_{\text{Occ-B}}\)  and \(\mathcal {L}_{\text{Occ-S}}\)  denote respectively the boundary detection and mask segmentation losses in the second GCN layer for the occludee, which are similar to Eq. REF  and Eq. REF . \(\mathcal {L}_{\text{Detect}}\)  supervises both the position prediction and the category classification borrowed from the FCOS [1]} detector,
\(\mathcal {L}_{\text{Detect}} = \mathcal {L}_{\text{Regression}} + \mathcal {L}_{\text{Centerness}} + \mathcal {L}_{\text{Class}},\) 
